Learning embedding features based on multi-sense-scaled attention architecture to improve the predictive performance of anticancer peptides.
Sign Up to like & getrecommendations! Published in 2021 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab560
Abstract: MOTIVATION Anticancer peptides (ACPs) have recently emerged as effective anticancer drugs in cancer therapy. Machine-learning-based predictors have been developed to identify ACPs and achieve satisfactory performance. However, existing methods suffer from experience-based feature engineering, which… read more here.
Keywords: anticancer peptides; dataset; acpred laf; predictive performance ... See more keywords